The spike aspartic acid-614 to glycine (D614G) substitution is prevalent in global severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains, but its effects on viral pathogenesis and ...transmissibility remain unclear. We engineered a SARS-CoV-2 variant containing this substitution. The variant exhibits more efficient infection, replication, and competitive fitness in primary human airway epithelial cells but maintains similar morphology and in vitro neutralization properties, compared with the ancestral wild-type virus. Infection of human angiotensin-converting enzyme 2 (ACE2) transgenic mice and Syrian hamsters with both viruses resulted in similar viral titers in respiratory tissues and pulmonary disease. However, the D614G variant transmits significantly faster and displayed increased competitive fitness than the wild-type virus in hamsters. These data show that the D614G substitution enhances SARS-CoV-2 infectivity, competitive fitness, and transmission in primary human cells and animal models.
A memristor
has been proposed as an artificial synapse for emerging neuromorphic computing applications
. To train a neural network in memristor arrays, changes in weight values in the form of device ...conductance should be distinct and uniform
. An electrochemical metallization (ECM) memory
, typically based on silicon (Si), has demonstrated a good analogue switching capability
owing to the high mobility of metal ions in the Si switching medium
. However, the large stochasticity of the ion movement results in switching variability. Here we demonstrate a Si memristor with alloyed conduction channels that shows a stable and controllable device operation, which enables the large-scale implementation of crossbar arrays. The conduction channel is formed by conventional silver (Ag) as a primary mobile metal alloyed with silicidable copper (Cu) that stabilizes switching. In an optimal alloying ratio, Cu effectively regulates the Ag movement, which contributes to a substantial improvement in the spatial/temporal switching uniformity, a stable data retention over a large conductance range and a substantially enhanced programmed symmetry in analogue conductance states. This alloyed memristor allows the fabrication of large-scale crossbar arrays that feature a high device yield and accurate analogue programming capability. Thus, our discovery of an alloyed memristor is a key step paving the way beyond von Neumann computing.
E-cigarettes vaporize propylene glycol/vegetable glycerin (PG/VG), nicotine, and flavorings. However, the long-term health effects of exposing lungs to vaped e-liquids are unknown.
To determine the ...effects of chronic vaping on pulmonary epithelia.
We performed research bronchoscopies on healthy nonsmokers, cigarette smokers, and e-cigarette users (vapers) and obtained bronchial brush biopsies and lavage samples from these subjects for proteomic investigation. We further employed in vitro and murine exposure models to support our human findings.
Visual inspection by bronchoscopy revealed that vaper airways appeared friable and erythematous. Epithelial cells from biopsy samples revealed approximately 300 proteins that were differentially expressed in smoker and vaper airways, with only 78 proteins being commonly altered in both groups and 113 uniquely altered in vapers. For example, CYP1B1 (cytochrome P450 family 1 subfamily B member 1), MUC5AC (mucin 5 AC), and MUC4 levels were increased in vapers. Aerosolized PG/VG alone significantly increased MUC5AC protein in human airway epithelial cultures and in murine nasal epithelia in vivo. We also found that e-liquids rapidly entered cells and that PG/VG reduced membrane fluidity and impaired protein diffusion.
We conclude that chronic vaping exerts marked biological effects on the lung and that these effects may in part be mediated by the PG/VG base. These changes are likely not harmless and may have clinical implications for the development of chronic lung disease. Further studies will be required to determine the full extent of vaping on the lung.
One broad goal of biomedical informatics is to generate fully-synthetic, faithfully representative electronic health records (EHRs) to facilitate data sharing between healthcare providers and ...researchers and promote methodological research. A variety of methods existing for generating synthetic EHRs, but they are not capable of generating unstructured text, like emergency department (ED) chief complaints, history of present illness, or progress notes. Here, we use the encoder-decoder model, a deep learning algorithm that features in many contemporary machine translation systems, to generate synthetic chief complaints from discrete variables in EHRs, like age group, gender, and discharge diagnosis. After being trained end-to-end on authentic records, the model can generate realistic chief complaint text that appears to preserve the epidemiological information encoded in the original record-sentence pairs. As a side effect of the model's optimization goal, these synthetic chief complaints are also free of relatively uncommon abbreviation and misspellings, and they include none of the personally identifiable information (PII) that was in the training data, suggesting that this model may be used to support the de-identification of text in EHRs. When combined with algorithms like generative adversarial networks (GANs), our model could be used to generate fully-synthetic EHRs, allowing healthcare providers to share faithful representations of multimodal medical data without compromising patient privacy. This is an important advance that we hope will facilitate the development of machine-learning methods for clinical decision support, disease surveillance, and other data-hungry applications in biomedical informatics.
The mode of acquisition and causes for the variable clinical spectrum of coronavirus disease 2019 (COVID-19) remain unknown. We utilized a reverse genetics system to generate a GFP reporter virus to ...explore severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogenesis and a luciferase reporter virus to demonstrate sera collected from SARS and COVID-19 patients exhibited limited cross-CoV neutralization. High-sensitivity RNA in situ mapping revealed the highest angiotensin-converting enzyme 2 (ACE2) expression in the nose with decreasing expression throughout the lower respiratory tract, paralleled by a striking gradient of SARS-CoV-2 infection in proximal (high) versus distal (low) pulmonary epithelial cultures. COVID-19 autopsied lung studies identified focal disease and, congruent with culture data, SARS-CoV-2-infected ciliated and type 2 pneumocyte cells in airway and alveolar regions, respectively. These findings highlight the nasal susceptibility to SARS-CoV-2 with likely subsequent aspiration-mediated virus seeding to the lung in SARS-CoV-2 pathogenesis. These reagents provide a foundation for investigations into virus-host interactions in protective immunity, host susceptibility, and virus pathogenesis.
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•A SARS-CoV-2 infectious cDNA clone and reporter viruses are generated•SARS-CoV-2 and SARS-CoV neutralization assays show limited cross neutralization•SARS-CoV-2 shows a gradient infectivity from the proximal to distal respiratory tract•Ciliated airway cells and AT-2 cells are primary targets for SARS-CoV-2 infection
Hou et al. present a reverse genetics system for SARS-CoV-2, which is then used to make reporter viruses to quantify the ability of patient sera and antibodies to neutralize infectious virus and to examine viral tropism along the human respiratory tract.
Coronavirus infection causes diffuse alveolar damage leading to acute respiratory distress syndrome. The absence of ex vivo models of human alveolar epithelium is hindering an understanding of ...coronavirus disease 2019 (COVID-19) pathogenesis. Here, we report a feeder-free, scalable, chemically defined, and modular alveolosphere culture system for the propagation and differentiation of human alveolar type 2 cells/pneumocytes derived from primary lung tissue. Cultured pneumocytes express the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) receptor angiotensin-converting enzyme receptor type-2 (ACE2) and can be infected with virus. Transcriptome and histological analysis of infected alveolospheres mirror features of COVID-19 lungs, including emergence of interferon (IFN)-mediated inflammatory responses, loss of surfactant proteins, and apoptosis. Treatment of alveolospheres with IFNs recapitulates features of virus infection, including cell death. In contrast, alveolospheres pretreated with low-dose IFNs show a reduction in viral replication, suggesting the prophylactic effectiveness of IFNs against SARS-CoV-2. Human stem cell-based alveolospheres, thus, provide novel insights into COVID-19 pathogenesis and can serve as a model for understanding human respiratory diseases.
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•Stroma-free long-term expansion and differentiation of adult human lung stem cells•AT2 response to SARS-CoV-2 infection mirrors features of COVID-19 lungs•Infected AT2s upregulate IFNs and apoptotic pathways and decrease surfactants•Low-dose IFN pre-treatment blocks SARS-CoV-2 replication in alveolospheres
Tata and colleagues report defined conditions for long-term expansion and differentiation of adult human primary alveolar stem cells. Cultured AT2s are conducive to SARS-CoV-2 infection and elicit transcriptome-wide changes that mirror COVID-19 histopathology, including upregulation of inflammatory responses, cell death, and downregulation of surfactant expression, leading to pneumocyte dysfunction.
Background The variability in functional outcomes and the occurrence of scapular notching and instability after reverse total shoulder arthroplasty remain problems. The objectives of this study were ...to measure the effect of reverse humeral component neck-shaft angle on impingement-free range of motion, abduction moment, and anterior dislocation force and to evaluate the effect of subscapularis loading on dislocation force. Methods Six cadaveric shoulders were tested with 155°, 145°, and 135° reverse shoulder humeral neck-shaft angles. The adduction angle at which bone contact occurred and the internal and external rotational impingement-free range of motion angles were measured. Glenohumeral abduction moment was measured at 0° and 30° of abduction, and anterior dislocation forces were measured at 30° of internal rotation, 0°, and 30° of external rotation with and without subscapularis loading. Results Adduction deficit angles for 155°, 145°, and 135° neck-shaft angle were 2° ± 5° of abduction, 7° ± 4° of adduction, and 12° ± 2° of adduction ( P < .05). Impingement-free angles of humeral rotation and abduction moments were not statistically different between the neck-shaft angles. The anterior dislocation force was significantly higher for the 135° neck-shaft angle at 30° of external rotation and significantly higher for the 155° neck-shaft angle at 30° of internal rotation ( P < .01). The anterior dislocation forces were significantly higher when the subscapularis was loaded ( P < .01). Conclusions The 155° neck-shaft angle was more prone to scapular bone contact during adduction but was more stable at the internally rotated position, which was the least stable humeral rotation position. Subscapularis loading gave further anterior stability with all neck-shaft angles at all positions.
The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive process to measure the prevalence of autism spectrum disorder (ASD) among children in the United States. Random ...forests methods have shown promise in speeding up this process, but they lag behind human classification accuracy by about 5%. We explore whether more recently available document classification algorithms can close this gap.
Using data gathered from a single surveillance site, we applied 8 supervised learning algorithms to predict whether children meet the case definition for ASD based solely on the words in their evaluations. We compared the algorithms' performance across 10 random train-test splits of the data, using classification accuracy, F1 score, and number of positive calls to evaluate their potential use for surveillance.
Across the 10 train-test cycles, the random forest and support vector machine with Naive Bayes features (NB-SVM) each achieved slightly more than 87% mean accuracy. The NB-SVM produced significantly more false negatives than false positives (P = 0.027), but the random forest did not, making its prevalence estimates very close to the true prevalence in the data. The best-performing neural network performed similarly to the random forest on both measures.
The random forest performed as well as more recently available models like the NB-SVM and the neural network, and it also produced good prevalence estimates. NB-SVM may not be a good candidate for use in a fully-automated surveillance workflow due to increased false negatives. More sophisticated algorithms, like hierarchical convolutional neural networks, may not be feasible to train due to characteristics of the data. Current algorithms might perform better if the data are abstracted and processed differently and if they take into account information about the children in addition to their evaluations.
Deep learning models performed similarly to traditional machine learning methods at predicting the clinician-assigned case status for CDC's autism surveillance system. While deep learning methods had limited benefit in this task, they may have applications in other surveillance systems.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Mutations in the cystic fibrosis transmembrane conductance regulator (
) gene cause the life-limiting hereditary disease, cystic fibrosis (CF). Decreased or absent functional CFTR protein in airway ...epithelial cells leads to abnormally viscous mucus and impaired mucociliary transport, resulting in bacterial infections and inflammation causing progressive lung damage. There are more than 2000 known variants in the
gene. A subset of CF individuals with specific
mutations qualify for pharmacotherapies of variable efficacy. These drugs, termed CFTR modulators, address key defects in protein folding, trafficking, abundance, and function at the apical cell membrane resulting from specific
mutations. However, some
mutations result in little or no CFTR mRNA or protein expression for which a pharmaceutical strategy is more challenging and remote. One approach to rescue CFTR function in the airway epithelium is to replace cells that carry a mutant
sequence with cells that express a normal copy of the gene. Cell-based therapy theoretically has the potential to serve as a one-time cure for CF lung disease regardless of the causative
mutation. In this review, we explore major challenges and recent progress toward this ambitious goal. The ideal therapeutic cell would: (1) be autologous to avoid the complications of rejection and immune-suppression; (2) be safely modified to express functional CFTR; (3) be expandable
to generate sufficient cell quantities to restore CFTR function; and (4) have the capacity to engraft, proliferate and persist long-term in recipient airways without complications. Herein, we explore human bronchial epithelial cells (HBECs) and induced pluripotent stem cells (iPSCs) as candidate cell therapies for CF and explore the challenges facing their delivery to the human airway.
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